We introduce a model to sequentially analyse both clinical trials and cost effectiveness of a new... more We introduce a model to sequentially analyse both clinical trials and cost effectiveness of a new health technology. This provides a consistent decision-making framework for evaluating (i) evidence from clinical trials, (ii) the expected value of further trials, (iii) the costs and benefits of adoption/abandonment. We derive the optimal decision rule by appropriately extending the Bayesian framework of sequential hypothesis testing. We find that increased noise in the trial observations lowers the value of the new technology, but leads to decisions, in expectation, being taken faster. The expected total discounted costs of the trial are non-monotonic in the incremental trial costs. The proposed method numerically outperforms a frequentist approach in terms of total value, and expected trial duration and costs. Delays in trial observations can have big qualitative effects on value. The model is illustrated using data on standard versus robot-assisted laporascopic prostatectomy.
In this paper we propose a solution to the Bayesian problem of a decision maker who chooses, whil... more In this paper we propose a solution to the Bayesian problem of a decision maker who chooses, while observing trial evidence, an optimal stopping time at which either to invest in a newly developed health care technology or abandon research. We show how optimal stopping boundaries can be computed as a function of the observed cumulative net benefit derived from the new health care technology. At the optimal stopping time, the decision taken is optimal and the decision maker either invest or abandon the technology with consequent health benefits to patients. The model takes into account the cost of decision errors and explicitly models these in the payoff to the heath care system. The implications in terms of opportunity costs of decisions taken at sub-optimal time is discussed and put in the value of information framework. In a case study it is shown that the proposed method, when compared with traditional ones, gives substantial economic gains both in terms of QALYs and reduced tria...
We introduce a model to sequentially analyse both clinical trials and cost effectiveness of a new... more We introduce a model to sequentially analyse both clinical trials and cost effectiveness of a new health technology. This provides a consistent decision-making framework for evaluating (i) evidence from clinical trials, (ii) the expected value of further trials, (iii) the costs and benefits of adoption/abandonment. We derive the optimal decision rule by appropriately extending the Bayesian framework of sequential hypothesis testing. We find that increased noise in the trial observations lowers the value of the new technology, but leads to decisions, in expectation, being taken faster. The expected total discounted costs of the trial are non-monotonic in the incremental trial costs. The proposed method numerically outperforms a frequentist approach in terms of total value, and expected trial duration and costs. Delays in trial observations can have big qualitative effects on value. The model is illustrated using data on standard versus robot-assisted laporascopic prostatectomy.
In this paper we propose a solution to the Bayesian problem of a decision maker who chooses, whil... more In this paper we propose a solution to the Bayesian problem of a decision maker who chooses, while observing trial evidence, an optimal stopping time at which either to invest in a newly developed health care technology or abandon research. We show how optimal stopping boundaries can be computed as a function of the observed cumulative net benefit derived from the new health care technology. At the optimal stopping time, the decision taken is optimal and the decision maker either invest or abandon the technology with consequent health benefits to patients. The model takes into account the cost of decision errors and explicitly models these in the payoff to the heath care system. The implications in terms of opportunity costs of decisions taken at sub-optimal time is discussed and put in the value of information framework. In a case study it is shown that the proposed method, when compared with traditional ones, gives substantial economic gains both in terms of QALYs and reduced tria...
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Papers by Jacco Thijssen